Training Portal

Indo-USA Online Short-term Course on "Application of Machine Learning to Wireless Communication"

Indo-USA Online Short-term Course on "Application of Machine Learning to Wireless Communication"

Schedule - January 21-24, 2022

Organized by - Indian Institute of Technology Bhubaneswar

Sponsored by - Scheme for Promotion of Academic and Research Collaboration (SPARC), MHRD, Govt. of India


About the Course

Communication system design has traditionally relied on developing a mathematical model and producing optimized algorithms for that model. However, with the increasing access to data and computing resources, a complementary data-driven approach based on machine learning has gained interest in recent years. This short course provides a brief introduction to machine learning that is tailored for communication and information theory researchers. The first module will provide an overview of statistical learning that will lead into the discussion of the types of communication system design problems that can benefit from machine learning. A case study exploring the connection of machine learning to point processes in the context of subset selection problems in wireless networks will also be presented. The second module will focus on statistical estimation. Popular supervised learning algorithms will be interpreted as ML and MAP estimators of appropriate underlying statistical models. The last two modules will focus on unsupervised learning, including discussions on k-means, expectation maximization, as well as detailed case studies related to distributed learning and codebook design in MIMO systems.



Who can attend?

UG, PG and Research Students

Academicians, doctors, researchers and engineers from Industries and R&D organizations.


Workshop Topics

  • Day-01: 21-01-2022 (Friday) (2Hrs)
    Time: 6:30 PM - 8:30 PM

    1. Introduction to Machine Learning and its role in Communications.
    2. Statistical Estimation and its Role in Machine Learning.
    3. Determinantal Learning for Subset Selection in Wireless Networks

    Name of the Speaker: Dr. Harpreet S Dhillon

  • Day-02: 22-01-2022 (Saturday) (4Hrs)
    Morning Session Time: 10 AM - 12 AM
    Evening Session Time: 6 PM - 8 PM

    1. Supervised Learning: Introduction, Interpretation as ML/MAP Estimators.
    2. Unsupervised Learning: Introduction, k-means, and Expectation Maximization.
    3. Case Study: Grassmann Clustering in Massive MIMO.

    Name of the Speaker: Dr. Harpreet S Dhillon

  • Day-03: 23-01-2022 (Sunday) (4Hrs)
    Morning Session Time: 10 AM - 12 PM

    1. Cognitive radio applications

    Name of the Speaker: Dr. M.S. Manikandan

  • Evening Session Time: 6 PM - 8 PM

    1. Density Estimation using GMM and Expectation Maximization.
    2. Gradient Compression for Federated Learning: A Wireless Perspective.
    3. Name of the Speaker: Dr. Harpreet S Dhillon